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研究生: 郭亭儀
Kuo, Ting-Yi
論文名稱: 波動擇時策略投資組合於台灣市場之因子投資組合之應用
Volatility Timing Strategies in Risk Factors of Taiwan Stock Market
指導教授: 郭維裕
Kuo, Wei-Yu
口試委員: 郭維裕
Kuo, Wei-Yu
徐政義
Shiu, Cheng-Yi
陳威光
Chen, Wei‑Kuang
學位類別: 碩士
Master
系所名稱: 商學院 - 國際經營與貿易學系
Department of International Business
論文出版年: 2020
畢業學年度: 108
語文別: 中文
論文頁數: 50
中文關鍵詞: 波動因子擇時策略槓桿
外文關鍵詞: Volatility, Factor, Timing Strategy, Leverage
DOI URL: http://doi.org/10.6814/NCCU202000654
相關次數: 點閱:145下載:10
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  • 全球化之盛行使各國市場連動性增強,而金融危機之發生使資產的報酬分配異常,促使投資人更謹慎管理投資組合之風險,而本研究將Liu, Tang and Zhou (2019)收錄的四個波動擇時策略,應用於台灣市場的七個因子風險溢酬之投資組合,發現考量條件資訊下之策略整體表現最好,而多數策略出現槓桿使用過大的問題,但使用槓桿限制後卻會對績效有負面影響;此外,針對極端經濟情況下,以虛擬變數觀察經濟衰退對於策略權重調整的影響,並以Garch(1,1)模擬資產報酬率,避免其波動率過大等分布異常問題。


    The prosperity of globalization has strengthened the market linkages of various countries, and the occurrence of the financial crisis has caused the abnormal distribution of asset returns, prompting investors to manage the risk of investment portfolios more carefully.
    This study implement the four volatility timing strategies of Liu, Tang and Zhou (2019) in seven factor portfolios of the Taiwan market. It’s found that the overall performance of the strategy under the conditional information is the best, and most strategies have the problem of excessive use of leverage, but the use of leverage limits has a negative impact on performance.
    In addition, for extreme economic conditions, observe the impact of economic recession on the adjustment of optimal weight of risky asset by using dummy variables. Then, use Garch(1,1) to simulate the assets return to avoid abnormal distribution problems such as excessive volatility.

    第一章 緒論 1
    第二章 研究方法 4
    第一節 波動率控制策略 4
    第二節 目標波動率策略 6
    第三節 估計風險下的平均數–變異數投資組合配置 7
    第四節 條件資訊下的最佳投資組合配置 8
    第三章 實證結果 9
    第一節 資料來源 9
    第二節 實證結果與分析 11
    一、 報酬率與波動率假設驗證 11
    二、 波動擇時策略績效比較 13
    三、 各因子的策略適用與槓桿限制應用 32
    四、 景氣循環對波動擇時策略之影響 37
    五、 Garch(1,1)於策略之應用 44
    第四章 結論 48
    參考文獻 50

    Barroso, P., and P. Santa-Clara. (2015) “Momentum Has Its Moments.” Journal of Financial Economics, 116 (1): 111–120.

    Basak, Gopal K. and Ma, Tongshu and Jagannathan, Ravi. (2004) “ A Jackknife Estimator for Tracking Error Variance of Optimal Portfolios Constructed Using Estimated Inputs“. NBER Working Paper, No. w10447.

    Ferson, W. E., and A. F. Siegel. (2001) “The Efficient Use of Conditioning Information in Portfolios.” Journal of Finance, 56 (3): 967–982.

    Han, Y., D. Huang, and G. Zhou. (2019) “Anomalies Enhanced: A Portfolio Re-Balancing Approach.” SSRN working paper.

    Hocquard, A., S. Ng, and N. Papageorgiou. (2013) “A Constant-Volatility Framework for Managing Tail Risk.” The Journal of Portfolio Management, Vol. 39, No. 2 , pp. 28-40.

    Kan, R., and G. Zhou. (2007) “Optimal Portfolio Choice with Parameter Uncertainty.” Journal of Financial and Quantitative Analysis, 42 (3): 621–656.

    F. Liu, X. Tang, G. Zhou. (2019) “Volatility-Managed Portfolio: Does It Really Work?”, The Journal of Portfolio Management, Vol. 46, (1) 38-51

    Moreira, A., and T. Muir. (2017) “Volatility-Managed Portfolios.” Journal of Finance, 72 (4): 1611–1644.

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